New Startup’s Legal Research App is Driven by Watson’s AI Technology

Casey Stengel had a very long, productive and colorful career in professional baseball as a player for five teams and later as a manager for four teams. He was also consistently quotable (although not to the extraordinary extent of his Yankee teammate Yogi Berra). Among the many things Casey said was his frequent use of the imperative “You could look it up”¹.

Transposing this gem of wisdom from baseball to law practice², looking something up has recently taken on an entirely new meaning. According to a fascinating article posted on Wired.com on August 8, 2015 entitled Your Lawyer May Soon Ask for This AI-Powered App for Legal Help by Davey Alba, a startup called ROSS Intelligence has created a unique new system for legal research. I will summarize, annotate and pose a few questions of my own.

One of the founders of ROSS, Jimoh Ovbiagele (@findingjimoh), was influenced by his childhood and adolescent experiences to pursue studying either law or computer science. He chose the latter and eventually ended up working on an artificial intelligence (AI) project at the University of Toronto. It occurred to him then that machine learning (a branch of AI), would be a helpful means to assist lawyers with their daily research requirements.

Mr. Ovbiagele joined with a group of co-founders from diverse fields including “law to computers to neuroscience” in order to launch ROSS Intelligence. The legal research app they have created is built upon the AI capabilities of IBM’s Watson as well as voice recognition. Since June, it has been tested in “small-scale pilot programs inside law firms”.

Essentially, the new ROSS app enables users to ask legal research questions in natural language. (See also the July 31, 2015 Subway Fold post entitled Watson, is That You? Yes, and I’ve Just Demo-ed My Analytics Skills at IBM’s New York Office.) Similar in operation to Apple’s Siri, when a question is verbally posed to ROSS, it searches through its data base of legal documents to provide an answer along with the source documents used to derive it. The reply is also assessed and assigned a “confidence rating”. The app further prompts the user to evaluate the response’s accuracy with an onscreen “thumbs up” or “thumbs down”. The latter will prompt ROSS to produce another result.

Andrew Arruda (@AndrewArruda), another co-founder of ROSS, described the development process as beginning with a “blank slate” version of Watson into which they uploaded “thousands of pages of legal documents”, and trained their system to make use of Watson’s “question-and-answer APIs³. Next, they added machine learning capabilities they called “LegalRank” (a reference to Google’s PageRank algorithm), which, among others things, designates preferential results depending upon the supporting documents’ numbers of citations and the deciding courts’ jurisdiction.

ROSS is currently concentrating on bankruptcy and insolvency issues. Mr. Ovbiagele and Mr. Arruda are sanguine about the possibilities of adding other practice areas to its capabilities. Furthermore, they believe that this would meaningfully reduce the $9.6 billion annually spent on legal research, some of which is presently being outsourced to other countries.

In another recent and unprecedented development, the global law firm Dentons has formed its own incubator for legal technology startups called NextLaw Labs. According to this August 7, 2015 news release on Denton’s website, the first company they have signed up for their portfolio is ROSS Intelligence.

Although it might be too early to exclaim “You could look it up” at this point, my own questions are as follows:

What pricing model(s) will ROSS use to determine the cost structure of their service?

Will ROSS consider making its app available to public interest attorneys and public defenders who might otherwise not have the resources to pay for access fees?

Will ROSS consider making their service available to the local, state and federal courts?

Should ROSS make their service available to law schools or might this somehow impair their traditional teaching of the fundamentals of legal research?

Will ROSS consider making their service available to non-lawyers in order to assist them in represent themselves on a pro se basis?

In addition to ROSS, what other entrepreneurial opportunities exist for other legal startups to deploy Watson technology?

Will other large law firms, as well as medium and smaller firms, and in-house corporate departments soon be following this lead?

Will they instead wait and see whether this produces tangible results for attorneys and their clients?

If so, what would these results look like in terms of the quality of legal services rendered, legal business development, client satisfaction, and/or the incentives for other legal startups to move into the legal AI space?